Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Análisis Temporal de Redes Sociales× | Análisis de Redes Sociales× | |
|---|---|---|
| Campo | Análisis de redes | Análisis de redes |
| Familia | Machine learning | Machine learning |
| Año de origen≠ | 2000s–2010s | 1934 (sociometry); 1994 (modern formalization) |
| Autor original≠ | Moody, J.; Holme, P.; Saramäki, J. | Moreno, J.L.; formalized by Wasserman & Faust |
| Tipo≠ | Longitudinal network analysis | Structural/relational analysis framework |
| Fuente seminal≠ | Holme, P., & Saramäki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125. DOI ↗ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 |
| Alias | TSNA, longitudinal social network analysis, time-varying network analysis, dynamic SNA | SNA, network analysis, sociometric analysis, relational analysis |
| Relacionados≠ | 4 | 5 |
| Resumen≠ | Temporal Social Network Analysis (TSNA) extends classic social network analysis by treating networks as time-varying structures. Rather than aggregating all ties into a single static snapshot, TSNA tracks when ties form, persist, and dissolve, enabling researchers to study how social structures evolve and how dynamic connectivity shapes diffusion, influence, and inequality over time. | Social Network Analysis (SNA) is a structural method that maps and measures relationships and flows between people, groups, organizations, or other entities modeled as nodes connected by ties (edges). Rather than focusing on individual attributes, SNA reveals how the pattern of connections shapes behavior, influence, information flow, and outcomes within a system. |
| ScholarGateConjunto de datos ↗ |
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